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Manager Causal Inference Jobs in Missouri (NOW HIRING)

Enterprise Holdings

Data Scientist

Saint Louis, MO · On-site

Louis, Enterprise Mobility together with its affiliate Enterprise Fleet Management manages a ... Apply causal inference techniques using observational data to uncover relationships * Prepare and ...

Enterprise Holdings

Data Scientist

Saint Louis, MO · On-site

Louis, Enterprise Mobility together with its affiliate Enterprise Fleet Management manages a ... Apply causal inference techniques using observational data to uncover relationships * Prepare and ...

Enterprise Holdings

Data Scientist

Saint Louis, MO

Louis, Enterprise Mobility together with its affiliate Enterprise Fleet Management manages a ... Apply causal inference techniques using observational data to uncover relationships * Prepare and ...

Walmart

(USA) Senior Manager, Data Science

Cassville, MO · On-site

$110K - $220K/yr

We are seeking a Senior Manager, Data Science to serve as the Technical Lead for this initiative ... Causal Inference: Ability to apply causal frameworks to observational data. * Forecasting & Anomaly ...

Walmart

(USA) Senior Manager, Data Science

Anderson, MO · On-site

$110K - $220K/yr

We are seeking a Senior Manager, Data Science to serve as the Technical Lead for this initiative ... Causal Inference: Ability to apply causal frameworks to observational data. * Forecasting & Anomaly ...

Walmart

(USA) Senior Manager, Data Science

Noel, MO · On-site

$110K - $220K/yr

We are seeking a Senior Manager, Data Science to serve as the Technical Lead for this initiative ... Causal Inference: Ability to apply causal frameworks to observational data. * Forecasting & Anomaly ...

Walmart

(USA) Director, Data Science

Noel, MO · On-site

$130K - $260K/yr

This leader will manage a high-performing team of Data Scientists and Machine Learning Engineers ... Identify opportunities to leverage AI, machine learning, causal inference, optimization, and ...

Walmart

(USA) Director, Data Science

Anderson, MO · On-site

$130K - $260K/yr

... causal inference to solve complex enterprise retail challenges. * Lead and Mentor: Champion a high-performing culture, managing and mentoring a talented team of data scientists, machine learning ...

Walmart

(USA) Director, Data Science

Anderson, MO · On-site

$130K - $260K/yr

This leader will manage a high-performing team of Data Scientists and Machine Learning Engineers ... Identify opportunities to leverage AI, machine learning, causal inference, optimization, and ...

Walmart

(USA) Director, Data Science

Cassville, MO · On-site

$130K - $260K/yr

This leader will manage a high-performing team of Data Scientists and Machine Learning Engineers ... Identify opportunities to leverage AI, machine learning, causal inference, optimization, and ...

Walmart

(USA) Director, Data Science

Noel, MO · On-site

$130K - $260K/yr

... causal inference to solve complex enterprise retail challenges. * Lead and Mentor: Champion a high-performing culture, managing and mentoring a talented team of data scientists, machine learning ...

Walmart

(USA) Director, Data Science

Cassville, MO · On-site

$130K - $260K/yr

... causal inference to solve complex enterprise retail challenges. * Lead and Mentor: Champion a high-performing culture, managing and mentoring a talented team of data scientists, machine learning ...

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Manager Causal Inference information

How does a Manager of Causal Inference typically collaborate with cross-functional teams to drive impactful business insights?

Managers of Causal Inference frequently work alongside data scientists, product managers, engineers, and business leaders to design and execute experiments that reveal the true impact of business decisions. They translate complex statistical findings into actionable recommendations, ensuring stakeholders understand both the methodology and implications. Regularly, they lead discussions on experiment design, data collection strategies, and result interpretation, fostering a culture of evidence-based decision-making across the organization.

What does a Manager Causal Inference do?

A Manager Causal Inference leads teams that analyze data to determine cause-and-effect relationships, often in business, healthcare, or technology settings. They design experiments or use statistical methods to understand how different factors influence outcomes, helping organizations make data-driven decisions. This role typically involves managing projects, overseeing analysts or data scientists, and communicating findings to stakeholders. Strong expertise in statistics, data analysis, and leadership is essential for success in this position.

What are the key skills and qualifications needed to thrive as a Manager of Causal Inference, and why are they important?

To thrive as a Manager of Causal Inference, you need a deep understanding of statistics, econometrics, and experimental design, typically supported by an advanced degree in a quantitative field. Proficiency with data analysis tools such as R, Python, SQL, and specialized causal inference libraries, along with experience using data visualization and project management platforms, is crucial. Strong leadership, communication, and critical thinking skills help you effectively guide teams and translate complex findings to stakeholders. These skills ensure rigorous, actionable insights that drive strategic decision-making and organizational impact.
What are the most commonly searched types of Causal Inference jobs in Missouri? The most popular types of Causal Inference jobs in Missouri are:
What are popular job titles related to Manager Causal Inference jobs in Missouri? For Manager Causal Inference jobs in Missouri, the most frequently searched job titles are:
What job categories do people searching Manager Causal Inference jobs in Missouri look for? The top searched job categories for Manager Causal Inference jobs in Missouri are:
Manager Causal Inference jobs near you
Data Scientist

Data Scientist

Enterprise Holdings

Saint Louis, MO • On-site

Full-time

Posted 17 days ago

Enterprise Holdings rating

7.2

Company rating: 7.2 out of 10

Based on 267 frontline employees who took The Breakroom Quiz

111th of 170 rated vehicle equipment hire

Job description

Overview
ABOUT THE COMPANY
Enterprise Mobility is a leading provider of mobility solutions, owning and operating the Enterprise Rent-A-Car, National Car Rental and Alamo Rent A Car brands through its integrated global network of independent regional subsidiaries. Enterprise Mobility and its affiliates offer extensive car rental, carsharing, truck rental, fleet management, retail car sales, as well as travel management and other transportation services, to make travel easier and more convenient for customers.
Privately held by the Taylor family of St. Louis, Enterprise Mobility together with its affiliate Enterprise Fleet Management manages a diverse fleet of 2.4 million vehicles and accounted for nearly $39 billion in revenue through a network of more than 9,500 fully-staffed neighborhood and airport rental locations in more than 90 countries and territories.
As we continue to build a team that drives us forward, we are excited to announce the opening for a Data Scientist.
ABOUT THE ROLE
The Data Scientist is a key driver of innovation, transforming data into actionable insights that improve business processes. In this role, you'll develop cutting-edge analytical products-creating algorithms for automation, building predictive models, designing experiments, and applying causal inference techniques to observational data. You'll also harness mathematical optimization to identify the most profitable business strategies. Success in this position requires strong collaboration with both technical and non-technical teams to ensure the creation, delivery, and adoption of impactful analytical solutions
This position is located at our Corporate Headquarters in Clayton, MO. This position is eligible for a hybrid work schedule.
Responsibilities
As a Data Scientist focused on revenue management, you will design and deploy advanced deep learning models to forecast demand. These models will enable branch-level decision-making, helping maximize revenue by leveraging historical trends and predictive analytics. In this role, you will collaborate closely with cross-functional teams to develop and implement analytical solutions that drive measurable business impact.
  • Collaborate with the team to design and deliver analytical solutions that drive business impact
  • Extract, clean, and manipulate structured and unstructured data from multiple sources
  • Perform exploratory data analysis to identify patterns, trends, and insights
  • Develop predictive models to support data-driven decision-making
  • Design and oversee experiments, ensuring accurate execution and interpretation of results
  • Apply causal inference techniques using observational data to uncover relationships
  • Prepare and deliver clear documentation of methodologies, findings, and recommendations
  • Create and present insightful reports and presentations for technical and non-technical audiences
  • Partner with cross-functional teams to implement and operationalize analytical solutions

Equal Opportunity Employer/Disability/Veterans
Qualifications
Required:
  • Must be presently authorized to work in the U.S. without a requirement for work authorization sponsorship by our company for this position now or in the future
  • Must reside in St. Louis, Missouri, or immediate surrounding area
  • Must have a Master's Degree in a Statistical or Mathematical field (e.g. Engineering, Social Science, or Statistics)
  • Must have two (2+) years of experience with predictive models, statistical inference and deep learning
  • Must have experience using libraries like tensorflow or pytorch
  • Must have experience preparing and giving presentations to technical and non-technical audiences
  • Must have proficiency in R or Python
  • Must be committed to incorporating security into all decisions and daily job responsibilities

Preferred:
  • Doctorate Degree in a Statistical or Mathematical field (e.g. Engineering, Social Science, or Statistics)
  • Experience designing experiments
  • Experience exploring and visualizing data
  • Experience using Linux/Unix
  • Experience using SQL
  • Experience working with data (merging, recording, etc.) from a variety of sources/formats
  • Experience working with observational data to attempt causal inference (e.g. matching, weighting, etc.)

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